# Replication materials for : More than Symbols : the effect of symbolic policies on support for costly climate policies

Authors: Théodore Tallent, Malo Jan, Luis Sattelmayer
Contact: malo.jan\@sciencespo.fr

This repository contains the code and data for the paper "More than Symbols: the effect of symbolic policies on support for costly climate policies". 


## Table of Contents

### Documentation Files
- `README_APSR.md` - This file
- `documentation/supplementary_material.pdf` - Appendix of the paper including : 
  - Pre-registration information and deviations from the pre-registration for Study 1 and Study 3
  - Details on survey samples and data collection for Study 1 and Study 3
  - Details on survey instrument and measures for Study 1 and Study 3
  - Details on the qualitative Study 2 including fieldwork context, qualitative methodology, positioning of the researchers, and coding procedure, interviewee characteristics, examples of interview excerpts, interview guide
- `documentation/ethic_approval.pdf` - Ethics approval for the entire research project

### Code Files

#### Master Scripts

- `code/00-setup-environment.R` - Sets up the renv environment for package management
- `code/full_replication.R` - **Complete replication pipeline** 

#### Analysis Scripts

- `code/01-study-01-cleaning.R` – Data cleaning for Study 1  
  - **Inputs:**
    - `data/raw/fr_cdsp_ddi_elipss_202312_bee.csv`
  - **Outputs:**
    - `data/processed/study-01-clean-data.rds`
    - `data/processed/study-01-climate-policy-support-data.rds`
    - `outputs/figures/appendix-figure-11.png`
    - `outputs/figures/appendix-figure-12.png`
    - `outputs/figures/appendix-figure-13.png`

- `code/02-study-01-descriptive.R` – Descriptive statistics for Appendix of Study 1  
  - **Inputs:**
    - `data/processed/study-01-clean-data.rds`
  - **Outputs:**
    - `outputs/figures/appendix-figure-01.pdf`
    - `outputs/figures/appendix-figure-02.pdf`
    - `outputs/figures/appendix-figure-03.pdf`
    - `outputs/figures/appendix-figure-04.pdf`
    - `outputs/figures/appendix-figure-05.pdf`
    - `outputs/figures/appendix-figure-06.pdf`
    - `outputs/figures/appendix-figure-07.pdf`
    - `outputs/figures/appendix-figure-08.pdf`
    - `outputs/figures/appendix-figure-09.pdf`
    - `outputs/figures/appendix-figure-10.pdf`
    
- `code/03-study-01-analysis.R` – Analysis for Study 1 (OLS models, tables, and figures)  
  - **Inputs:**
    - `data/processed/study-01-clean-data.rds`
  - **Outputs:**
    - `data/processed/study-01-ols-coefficients.rds`
    - `data/processed/study-01-outcome-distribution.rds`
    - `data/processed/study-01-predictions-ols-int-behavior.rds`
    - `data/processed/study-01-predictions-ols-int-ideology.rds`
    - `data/processed/study-01-predictions-ols-int-policy-support.rds`
    - `outputs/figures/figure-01.pdf`
    - `outputs/figures/figure-02.pdf`
    - `outputs/figures/appendix-figure-14.png`
    - `outputs/figures/appendix-figure-15.png`
    - `outputs/figures/appendix-figure-16.png`
    - `outputs/tables/appendix-tbl-01.tex`
    - `outputs/tables/appendix-tbl-02.tex`
    - `outputs/tables/appendix-tbl-03.tex`
    - `outputs/tables/appendix-tbl-04.tex`
    - `outputs/tables/appendix-tbl-05.tex`
    - `outputs/tables/appendix-tbl-06.tex`
    
  
- `code/04-study-03-cleaning.R` – Data cleaning for Study 3  
  - **Inputs:**
    - `data/raw/study-03-data-raw.sav`
  - **Outputs:**
    - `data/processed/study-03-clean-data.rds`

- `code/05-study-03-descriptives.R` – Descriptive statistics for Appendix of Study 3  
  - **Inputs:**  
    - `data/processed/data-study-03-clean.rds`  
  - **Outputs:**  
    - `outputs/figures/appendix-figure-17.pdf`  
    - `outputs/figures/appendix-figure-18.pdf`  
    - `outputs/figures/appendix-figure-19.pdf`  
    - `outputs/figures/appendix-figure-20.pdf`  
    - `outputs/figures/appendix-figure-21.pdf`  
    - `outputs/figures/appendix-figure-22.pdf`  
    - `outputs/figures/appendix-figure-23.pdf`  
    - `outputs/figures/appendix-figure-24.pdf`  
    - `outputs/figures/appendix-figure-25.pdf`
  
- `code/06-study-03-analysis.R` – Analysis for Study 3 (OLS models, tables, and figures)  
  - **Inputs:**  
    - `data/processed/study-03-clean-data.rds`  
  - **Outputs:**  
    - `data/processed/study-03-ols-coefficients.rds`  
    - `outputs/tables/appendix-tbl-08.tex`  
    - `outputs/tables/appendix-tbl-09.tex`  
    - `outputs/tables/appendix-tbl-10.tex`  
    - `outputs/tables/appendix-tbl-11.tex`  
    - `outputs/tables/appendix-tbl-12.tex`  
    - `outputs/figures/figure-03.pdf`  
    - `outputs/figures/figure-04.pdf`  
    - `outputs/figures/figure-05.pdf`
  
### Data Files

#### Raw data files

- `data/raw/fr_cdsp_ddi_elipss_202312_bee.csv` - Raw data for Study 1 (to be downloaded from [data.sciencespo.fr](https://doi.org/10.21410/7E4/OH0RKI))
- `data/raw/study-03-data-raw.sav` - Raw data for Study 2

### Processed data files

- `data/processed/study-01-clean-data.rds` - Cleaned data for Study 1 (generated by `01-study-01-cleaning.R`)
- `data/processed/study-01-climate-policy-support-data.rds` - Data on climate policy support for Study 1 (generated by `01-study-01-cleaning.R`)
- `data/processed/study-01-ols-coefficients.rds` - OLS model coefficients for Study 1 (generated by `03-study-01-analysis.R`)
- `data/processed/study-01-outcome-distribution.rds` - Outcome distribution data for Study 1 (generated by `03-study-01-analysis.R`)
- `data/processed/study-01-predictions-ols-int-behavior.rds` - OLS predictions for behavior outcome in Study 1 (generated by `03-study-01-analysis.R`)
- `data/processed/study-01-predictions-ols-int-ideology.rds` - OLS predictions for ideology outcome in Study 1 (generated by `03-study-01-analysis.R`)
- `data/processed/study-01-predictions-ols-int-policy-support.rds` - OLS predictions for policy support outcome in Study 1 (generated by `03-study-01-analysis.R`)
- `data/processed/study-03-clean-data.rds` - Cleaned data for Study 3 (generated by `04-study-03-cleaning.R`)
- `data/processed/study-03-ols-coefficients.rds` - OLS model coefficients for Study 3 (generated by `06-study-03-analysis.R`)

#### Outputs

- `outputs/` - Generated figures (PDF) and tables (LaTeX)

### Reproducibility Environment Files

These files ensure that all analyses can be fully replicated using the same R package versions and system configuration.

- `renv.lock` – Defines the exact versions of all R packages used across the project.  
- `renv/` – Contains metadata and bootstrap scripts required for `renv` to function 


## Replication instructions

### Setup
1. Clone or download this repository
2. Open the Rproject `symbolic_climate_policy.Rproj` in *Rstudio** or Set working directory to the repository root
3. Run the following script to install and load the `renv` package, which manages the project environment:

```r
source("code/00-setup-environment.R")
```

### Option 1 : Complete Replication (Recommended)

Once the environment is set up, you can run the entire replication workflow with a single command that will execute all the scripts to clean the raw data and produce all results: 
```r
source("code/full_replication.R")
```
To run the complete replication, the Study 1 data file `fr_cdsp_ddi_elipss_202312_bee.csv` has to be downloaded from [data.sciencespo.fr](https://doi.org/10.21410/7E4/OH0RKI) and placed in the `data/raw/` folder. The data for Study 2 are already included in this repository under `data/raw/`.

## Option 2: Run individual scripts

Alternatively, you can run the scripts for each study individually to replicate specific parts of the analysis, after setting up the environment as described above.

To replicate Study 1, the data file `fr_cdsp_ddi_elipss_202312_bee.csv` has to be requested and downloaded from [data.sciencespo.fr](https://doi.org/10.21410/7E4/OH0RKI) and placed in the `data/raw/` folder. The analysis can be replicated by running the following scripts in order. Note that the second and third scripts require the output generated by the first script to run properly.

```r
source("01-study-01-cleaning.R")
source("02-study-01-descriptives.R")
source("03-study-01-analysis.R")
```

To replicate Study 3, run the following scripts in order. The second and third scripts require the output of the first script to run properly. However, this output is already included in the repository, so scripts 05 and 06 can also be run directly if desired.

```r
source("04-study-02-cleaning.R")
source("05-study-02-descriptives.R")
source("06-study-02-analysis.R")
```

In both cases, the generated figures and tables will be saved in the `outputs/` folder with the table and figure numbers corresponding to those in the paper.

## Data and Code Availability Statement

- Study 1 data were collected as part of the Ecology and Environment Barometer through the ELIPSS panel managed by Sciences Po’s Centre for Socio-Political Data (CDSP). The data are freely available for research purposes to individuals with an academic affiliation. To access the data, users must create an account on the data.sciencespo.fr
 Dataverse, submit a request, and download the files once approval is granted. The raw dataset, `fr_cdsp_ddi_elipss_202312_bee.csv`,  collected as part of this study and used in this paper, is stored at the following address: https://doi.org/10.21410/7E4/OH0RKI . Once downloaded, the data file should be placed in the `data/raw/` folder of this repository to run the replication code.

- Study 3 data were collected for the purposes of this research through a survey experiment administered by the access panel provider Bilendi. The raw data from this survey including all variables collected are included in this repository under `data/raw/study-03-data-raw.sav`.

## Computational Requirements

### Computations were conducted using a : 

- Apple MacBook Air M1 (2023)
   - 16 GB
   - macOS: 26.0
   - R version 4.3.1 (2023-06-16)

### R packages and their versions

| Package     | Version |
|--------------|---------|
| here         | 1.0.2   |
| tidyverse    | 2.0.0   |
| gretlR       | 0.1.4   |
| scales       | 1.4.0   |
| factoextra   | 1.0.7   |
| FactoMineR   | 2.12    |
| haven        | 2.5.5   |
| rmarkdown    | 2.30    |
| renv         | 1.1.4   |
| glue         | 1.8.0   |
| janitor      | 2.2.1   |
| broom        | 1.0.10  |
| ggeffects    | 2.3.1   |
| stargazer    | 5.2.3   |
| stringr      | 1.5.2   |
| purrr        | 1.1.0   |

### Hardware requirements

- CPU: Any modern processor (e.g., Intel i3 / AMD Ryzen 3 or higher)
- RAM: 4 GB minimum, 8 GB recommended
- Storage: At least 1 GB of free disk space
- Internet: Required only for installing R packages or downloading data

### Contact Information
For questions about the replication materials, please contact:
- **Malo Jan**: [malo.jan@sciencespo.fr](mailto:malo.jan@sciencespo.fr) 
- **Luis Sattelmayer**: [luis.sattelmayer@sciencespo.fr](mailto:luis.sattelmayer@sciencespo.fr) 
- **Théodore Tallent**: [theodore.tallent@sciencespo.fr](mailto:theodore.tallent@sciencespo.fr) 

## Citation

If you use the code, data and replication material, please cite:
Tallent, T., Jan, M., & Sattelmayer, L. (2025). More than Symbols : the effect of symbolic policies on support for costly climate policies. American Political Science Review.

If you use data from Study 1, please also cite:

``` bibtex

@data{7E4/OH0RKI_2024,
author = {Éric Pautard and Nicolas Sauger and Luc Rouban and Maël Ginsburger and Emiliano Grossman and Malo Jan and Luis Sattelmayer and Théodore Tallent and Lucien Thabourey and Simon Audebert},
publisher = {data.sciencespo},
title = {{Baromètre Écologie Environnement (ELIPSS 2023)}},
UNF = {UNF:6:uM9F77QUEn43nBVo9HlrDQ==},
year = {2024},
version = {V2},
doi = {10.21410/7E4/OH0RKI},
url = {https://doi.org/10.21410/7E4/OH0RKI}
}
```
